Identifying ATT&CK Tactics in Android Malware Control Flow Graph through Graph Representation Learning and Interpretability (Student Abstract)
Keywords:Control Flow Graphs, Graph Representation Learning, Interpretability, ATT&CK Tactics
AbstractTo mitigate a malware threat it is important to understand the malware’s behavior. The MITRE ATT&ACK ontology specifies an enumeration of tactics, techniques, and procedures (TTP) that characterize malware. However, absent are automated procedures that would characterize, given the malware executable, which part of the execution flow is connected with a specific TTP. This paper provides an automation methodology to locate TTP in a sub-part of the control flow graph that describes the execution flow of a malware executable. This methodology merges graph representation learning and tools for machine learning explanation.
How to Cite
Fairbanks, J., Orbe, A., Patterson, C., Serra, E., & Scheepers, M. (2022). Identifying ATT&CK Tactics in Android Malware Control Flow Graph through Graph Representation Learning and Interpretability (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12941-12942. https://doi.org/10.1609/aaai.v36i11.21607
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